Wastewater-Based Surveillance of SARS-CoV-2 for Early Warning of COVID-19 Infection Dynamics.

Wastewater-based epidemiology has emerged as a valuable complementary tool for population-level monitoring. This study evaluated the early warning value of wastewater surveillance for monitoring SARS-CoV-2 and its correlation with COVID-19 infection trends. From May 2024 to December 2025, 526 wastewater samples were collected from five treatment plants. Spearman correlation and a quasi-Poisson generalized additive model (adjusting for wastewater temperature) were used to assess relationships between SARS-CoV-2 RNA concentration, the number of reported cases, and lag associations. Wastewater viral loads (copies/mL) significantly correlated with reported cases. Wastewater temperature was positively correlated with both viral concentrations and case numbers. A significant lagged association was observed for the N gene, with relative risk peaking at a 10-day lag. Although the ORF1ab gene was not significant for most lag periods, its temporal trend was consistent with that of the N gene. Wastewater surveillance of SARS-CoV-2, particularly targeting the N gene, can effectively predict COVID-19 infection dynamics with a 10-day lead time, thereby supporting wastewater surveillance as an early warning tool for public health monitoring.